Jeong Heon Lee, Kai Bao, John V Frangioni, Hak Soo Choi
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引用次数: 2
Abstract
The screening of living cells using high-throughput microarrays is technically challenging. Great care must be taken in the chemical presentation of potential ligands and the number of collisions that cells make with them. To overcome these issues, we have developed a glass slide-based microarray system to discover small molecule ligands that preferentially bind to one cell type over another, including when the cells differ by only a single receptor. Chemical spots of 300 ± 10 μm in diameter are conjugated covalently to glass slides using an arraying robot, and novel near-infrared fluorophores with peak emission at 700 nm and 800 nm are used to label two different cell types. By carefully optimizing incubation conditions, including cell density, motion, kinetics, detection, etc. we demonstrate that cell-ligand binding occurs, and that the number of cells bound per chemical spot correlates with ligand affinity and specificity. This screening system lays the foundation for high-throughput discovery of novel ligands to the cell surface.
期刊介绍:
High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.